Inverse cutting plane methods for optimization problems with second-order stochastic dominance constraints

被引：17

作者：

Dentcheva, Darinka ^{[1
]}

Ruszczynski, Andrzej ^{[2
]}

机构：

[1] Stevens Inst Technol, Dept Math Sci, Hoboken, NJ 07030 USA

[2] Rutgers State Univ, Dept Management Sci & Informat Syst, Piscataway, NJ 08854 USA

来源：

OPTIMIZATION | 2010年 / 59卷 / 03期

基金：

美国国家科学基金会;

关键词：

stochastic dominance; cutting plane methods; Lorenz curve; portfolio optimization; conditional value-at-risk; DUALITY; RISK;

D O I：

10.1080/02331931003696350

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We propose new cutting plane methods for solving optimization problems with second-order stochastic dominance constraints. The methods are based on the inverse formulation of stochastic dominance constraints using Lorenz functions. Convergence of the methods is proved for general probability distributions. For general discrete distributions convergence is finite. Numerical experiments on a portfolio problem confirm efficiency of the methods.

引用

页码：323 / 338

页数：16

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